L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...